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Record W3006015500 · doi:10.1093/ptj/pzz175

Assessing Arm Volume in People During and After Treatment for Breast Cancer: Reliability and Convergent Validity of the LymphaTech System

2020· article· en· W3006015500 on OpenAlexaff
Jill Binkley, Michael Weiler, Nathan D. Frank, Lauren Bober, J. Brandon Dixon, Paul W. Stratford

Bibliographic record

VenuePhysical Therapy · 2020
Typearticle
Languageen
FieldMedicine
TopicLymphatic System and Diseases
Canadian institutionsMcMaster University
Fundersnot available
KeywordsIntraclass correlationConvergent validityBreast cancerLymphedemaInter-rater reliabilityReliability (semiconductor)Intra-rater reliabilityContext (archaeology)Standard errorPhysical therapyMedicinePsychologyStatisticsReproducibilityPsychometricsConfidence intervalMathematicsCancerInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: There are challenges related to the accurate and efficient measurement of lymphedema in people with breast cancer. The LymphaTech 3D Imaging System (LymphaTech, Atlanta, GA, USA) is a mobile, noninvasive platform that provides limb geometry measurements. OBJECTIVE: The objective of this study was to estimate the reliability and validity of the LymphaTech for measuring arm volume in the context of women seeking care in a specialty breast cancer rehabilitation clinic. DESIGN: This was a cross-sectional reliability and convergent validity study. METHODS: People who had stage I to IV breast cancer with lymphedema or were at risk for it were included. Arm volume was measured in 66 participants using the LymphaTech and perometer methods. Test-retest reliability for a single measure, limb volume difference, and agreement between methods was analyzed for 30 participants. A method-comparison analysis was also used to assess convergent validity between methods. RESULTS: Both LymphaTech and perometer methods displayed intraclass correlation coefficients (ICCs) of ≥0.99. The standard errors of measurement for the LymphaTech and length-matched perometer measurements were nearly identical. Similar intraclass correlation coefficients (0.97) and standard errors of measurement (38.0-40.7 mL) were obtained for the between-limb volume difference for both methods. The convergent validity analyses demonstrated no systematic difference between methods. LIMITATIONS: The sample size was not based on a formal sample size calculation. LymphaTech measurements included interrater variance, and perometer measurements contained intrarater variance. CONCLUSIONS: The LymphaTech had excellent test-retest reliability, and convergent validity was supported. This technology is efficient and portable and has a potential role in prospective surveillance and management of lymphedema in clinical, research, and home settings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.305
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2020
Admission routes1
Has abstractyes

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